Robust Mechanism Synthesis with Random and Interval VariablesMechanism and Machine Theory
AbstractRobust mechanism synthesis minimizes the impact of uncertainties on the mechanism performance. It has traditionally been performed by either a probabilistic approach or a worst case approach. Both approaches treat uncertainty as either random variables or interval variables. In reality, uncertainty can be a mixture of both. In this paper, methods are developed for robustness assessment and robust mechanism synthesis when random and interval variables are involved. Monte Carlo simulation is used to perform robustness assessment under an optimization framework for mechanism synthesis.
Department(s)Mechanical and Aerospace Engineering
Sponsor(s)Missouri University of Science and Technology. Intelligent Systems Center
National Natural Science Foundation (China)
National Science Foundation (U.S.)
Keywords and Phrases
Document TypeArticle - Journal
Rights© 2009 Elsevier, All rights reserved.
Citation InformationXiaoping Du, Pavan Kumar Venigella and Deshun Liu. "Robust Mechanism Synthesis with Random and Interval Variables" Mechanism and Machine Theory (2009)
Available at: http://works.bepress.com/xiaoping-du/71/